Parkinson's disease (PD) is a common disease of aging that causes motor symptoms such as slow movement and tremor, as well as non-motor symptoms, such as cognitive decline. The motor symptoms are progressive, and often begin on one side of the body. Motor symptoms become detectable only when a large proportion of cells that manufacture the neurotransmitter dopamine have died. Although we currently have neuroimaging biomarkers for dopamine cells, we do not fully understand how loss of these cells influences brain functional and structural networks to give rise to symptoms. In recent years, magnetic resonance imaging (MRI) techniques have made it possible to begin mapping the human connectome - i.e., mapping the structural and functional connections between brain regions that form neural networks. Slow, synchronous fluctuations in blood oxygen dependent signal across the cerebrum can be used to map functional networks (fcMRI), while diffusion tensor imaging (DTI) is used to measure the microstructural health of nerve fibers and to extrapolate tracks between neuronal groups. The focus of this proposal will be to use these non-invasive techniques to map functional and structural connectivity changes in the brains of patients with PD, and to relate these changes to clinical symptoms. With prior VA funding through a career development mechanism, the PI gathered pilot MRI data from 15 PD subjects that were compared with control data. Analysis of the fcMRI suggested that two specific networks that link the cerebral cortex with different movement centers interact abnormally in PD. The DTI data suggested that PD also affects the neuronal processes that connect brain regions as nodes in these networks. Our recent work also showed that these DTI changes are related to cognitive function. We plan to extend and validate these findings in a larger sample. Hypotheses: The overall hypotheses are that metrics derived from DTI and fcMRI images will explain the nature and severity of motor and cognitive symptoms of PD. The longitudinal design will identify MRI measures that predict the rate of clinical symptom progression, and the transition from symptoms on one side of the body to both sides of the body. Study Design: This 4-year project will prospectively gather detailed clinical, cognitive, and MRI measures at time points two years apart. Sixty veterans with early PD and twenty healthy, age-matched controls will be recruited through VA clinics and studied as a longitudinal cohort. Study procedures will include brain MRI for network measures, as well as detailed neuropsychological and clinical assessments at two-year intervals. The specific aims are as follows: Aim 1: Measure key functional interactions between two brain networks that have roles in movement and cognition, and determine to what degree these measures reflect the nature and severity of motor and cognitive symptoms in PD. Aim 2: Determine to what degree microstructural and visible changes in the white matter that support these networks are related to clinical symptoms. Aim 3: Identify MRI measures of functional and structural networks that predict the rate and quality of clinical disease progression. The strong preliminary data we present in this application show that our research team has refined the techniques that will be needed to efficiently gather and analyze data for this prospective study. Significance for Veterans: PD currently affects 60,000 VA patients, and this number is expected to grow as veterans who served in the Vietnam era enter peak ages for onset of the disease. This project will be a first step in identifying new candidate biomarkers to be used in clinical trials.